🎒
NGS for natural scientist
  • 1. Preface
    • How to use this book
    • Motivation
    • Genomic data science as a tool to biologist
    • Next Generation Science (also NGS)
  • 2. Getting started
    • A step by step pipeline tutorial
    • Sequencing chemistry explained by Illumina
    • Joining a course
    • RNA quality and Library prep
    • (optional) My click moment about "Why Linux"
  • 3. Good-to-know beforehand
    • Experiment design
    • Single-end and Paired-end
    • Read per sample and data size
    • Normalization - RPKM/FPKM/TPM
    • Gene annotation
  • 4. Setting up terminal
    • My Linux terminal
    • Linux environment
    • R and RStudio
    • PATH
  • 5. FASTQ and quality control
    • Getting FASTQ files from online database
    • FASTQ quality assessment
  • 6. Mapping/alignment and quantification
    • Salmon
    • DESeq2
  • 7. Visualization
  • 8. Single cell RNA-Seq
  • 9. AWS cloud and Machine Learning
    • Machine Learning in a nutshell
    • R vs Python
    • Setting up ML terminal
    • Data exploration
  • (pending material)
    • graphPad
    • readings for ML
Powered by GitBook
On this page

(pending material)

They will disappear in the final edition, if there is any. I won't be surprised, however, if you can make use of them.

PreviousData explorationNextgraphPad

Last updated 2 years ago

graphPad
readings for ML